Harmonizing and combining existing land cover and land use datasets for cropland areas monitoring at the African continental scale

Mapping cropland areas is of great interest in diverse fields, from crop monitoring to climate change and food security. Recognizing the value of a reliable and harmonized crop mask that entirely covers the African continent, the objectives of this study were to (i) consolidate the best existing land cover/land use datasets, (ii) adopt the Land Cover Classification System (LCCS) for harmonization and (iii) assess the final product. Ten datasets were compared and combined through an expert-based approach to create the derived map of cropland areas at 250m covering the whole of Africa. The resulting cropland mask was compared with two recent cropland extent maps at 1km: one derived from MODIS and one derived from five existing products. The accuracy of the three products was assessed against a validation sample of 3591 pixels of 1km² regularly distributed over Africa and interpreted using high resolution images, which were collected using the agriculture.geo.wiki.org tool. The comparison of the resulting crop mask with existing products shows that it has a greater agreement with the expert validation dataset, in particular for cropland above 30%.